Other

Niramai Health Analytix Pvt Ltd

Siva Teja Kakileti

Geetha Manjunath

Himanshu Jayantkumar Madhu

Krithika Venkataramani

Arun Koushik Parthasarathy

Susmija Jabbireddy

Hadonahalli V Ramprakash

Minerva Panda

Himanshu Jayant Kumar Madhu

V N Ratna Kumari T

Gayatri Sivakumar

Kanchana Gopinath

Shubhi Sharma

A method for identifying errors associated with subject positioning in a thermal image of a subject and determining, applying a positional adjustment for adaptive positioning of the subject for capturing a new adjusted thermal image. The method includes (i) receiving an initial thermal image of body of a subject, (ii) automatically segmenting breast region from the initial thermal image, (iii) computing a plurality of positions and a plurality of deviations in the plurality of positions using a thermal imaging protocol, (iv) determining a positional adjustment to be made to a position of thermal imaging camera or a position of the subject based on the plurality of deviations in the plurality of positions of the breast region and (v) applying the positional adjustment for adjusting a position of the thermal imaging camera or subject for capturing a new adjusted thermal image at the required position as per thermal imaging protocol.

System and method for identifying errors in positioning of a subject for capturing a thermal image

A system and method for a quantitative evaluation of a breast health of a pregnant and lactating woman for clinical management of a breast feeding by performing (i) receiving a thermal image of a breast region of the pregnant and lactating woman, (ii) automatically determine network structures associated with ductal or vascular thermal patterns of the pregnant and lactating woman by analysing the thermal images of the pregnant and lactating woman, (iii) estimate quantitative parameters corresponding to the network structures associated with the ductal or vascular thermal patterns using the machine learning model and (iv) generate a breast health report with the estimated quantitative parameters and the schematics of vascular network to enable clinical management of breastfeeding.

System and method for quantitative evaluation of breast health

A system and method for automatically detecting a location of a plurality of hotspots from a thermal image of a breast region of a subject by (i) automatically detecting areolar points (x, y) from the thermal image of the breast region of the subject, (ii) automatically detecting a plurality of hotspot regions on the thermal image of the breast region of the subject by performing a hotspot region segmentation method, (iii) calculating a plurality of radial locations (ri, θi) of a plurality of hotspots on the hotspot region, (iv) automatically generating a text report based on the detected location of the plurality of hotspots and (v) providing the detected radial locations (ri, θi) of the plurality of hotspots as a text report to scan the plurality of hotspots only on the detected radial locations (ri, θi) instead of scanning in the entire breast region of the subject.

System and method of automatic detection of hotspot locations in breast thermograms

A system and method for processing values of a subset of numeric features to provide interpretability of the results of a machine learning model, by determining an extent of the contribution of the subset of features towards a predicted class by performing: (i) receiving the thermal image, (ii) obtaining a region of interest in the thermal image of the subject, (iii) extracting a plurality of numeric features associated with the region of interest of the thermal image, (iv) predicting a class, (v) estimate an extent of contribution of the subset of numeric features towards the decision of the first machine learning prediction model (M) and (vi) generate a report that includes a generated discrete values that determines the extent of contribution of the subset of numeric features towards the predicted class.

System and method to generate discretized interpretable features in machine learning model

A method for determining a view angle of a thermal image from a user and generating a suggestion to enable the user for adaptive positioning of a subject for capturing the thermal image is provided. The method includes (i) receiving a thermal image of a body of a subject, (ii) automatically determining a view angle of the thermal image from a user using a view angle estimator, (iii) determining an angular adjustment to be made to a view position of the thermal imaging camera or a position of the subject by comparing the determined view angle with a required view angle as per thermal imaging protocol when the thermal image does not meet the required view angle and (iv) generating instructions to the user for adjusting the view position of the thermal imaging camera for capturing a new thermal image at the required view angle as per thermal imaging protocol.

System and method for adaptive positioning of a subject for capturing a thermal image

What is disclosed is an apparatus for enabling privacy for patients undergoing breast cancer screening in a non-clinical setting. One embodiment of the present apparatus comprises an enclosure in which a person can remove one or more garments to expose their breasts to a thermal camera for breast cancer screening. The enclosure is such that at least the breast area of that person is shielded from view by third parties. The apparatus also comprises a thermal camera for capturing thermal images of the exposed breast area. The thermal camera is connected to a robotic arm that changes the camera angle relative to real-world coordinates so that thermal images can be taken of the breast area from any angle between a frontal view and a left/right lateral view. A processor which executes a software interface tool for semi-automated or automated breast cancer screening based on the thermal images of the breast.

Privacy booth for breast cancer screening

What is disclosed is a system and method for classifying the hormone receptor status of malignant tumorous tissue identified in a thermographic image of a breast. One embodiment of the present method involves the following. First, receive thermographic image(s) of both breasts of a patient with a malignant tumorous region and analyzing the image(s) to define a boundary contour of the breast. Then, the breast regions are segment into regions of elevated temperature. A function of first probability mass function Q, &#x192;(Q), is determined based on temperatures of pixels within a first segmented region. A function of the second probability mass function P, &#x192;(P), is determined based on temperatures of pixels within a second region. A distance measure between the two functions &#x192;(Q) and &#x192;(P) is calculated and provided to a classifier trained to classify the malignant tissue as hormone receptor positive, and negative otherwise, based on the distance measure.

Classifying hormone receptor status of malignant tumorous tissue from breast thermographic images

What is disclosed is a system and method for breast cancer screening which determines whether hot spots, as seen in a thermal image of both breasts, can be classified as possibly malignant based on a measure of symmetry. A thermographic image of both breasts of a patient is received and analyzed to determine whether there exists, in each of a left breast and a right breast, a hot spot comprising a patch of pixels with an elevated temperature with respect to surrounding tissue. If a hot spot has been identified in each breast then a measure of symmetry comprising a ratio of an area of a smaller hot spot to an area of a larger hot spot is extracted from the thermographic image. The measure of symmetry is provided to a classifier system trained to classify an unclassified hot spot as malignant or non-malignant based on a measure of symmetry.

Thermography-based breast cancer screening using a measure of symmetry

What is disclosed is a system and method for isolating blood vessels in a thermographic image of a patient's breast or any other muscular region of the body. A thermographic image of a patient is received. A temperature-based analysis is performed on the image to detect vessel pixels. An intensity-based method analysis is performed on the image. A shape-based analysis is also performed to detect pixels of vessel-like structures. Candidate pixels which satisfy one or more of intensity-based or temperature-based or shaped-based criterion are identified. A constraint of local maximallity is thereafter imposed on each candidate pixel that satisfies both criterion to eliminate spurious non-vessel pixels. Candidate pixels which satisfy both criterion are then marked with a different color such that the vessel structures in the breast tissue can be visually differentiated. The vessel structures are provided to a classifier system which classifies the tissue in the thermal image as malignant and non-malignant otherwise, based on a tortuosity of the vessel structures.

Blood vessel extraction in two-dimensional thermography

What is disclosed is a system and method for automatically segmenting a breast from surrounding tissue in a thermal image. A thermal image of at least one breast of the patient is received. The thermal image is then analyzed to identify a set of N points around the breast, a contour of an outline of the body, and isotherms of the axilla and infra-mammary fold. Thereafter, the points are connected together to form a N-sided irregular polygon which segments the breast from surrounding tissue. Each of the points is a vertex of the polygon and comprises a draggable object which enables a user to selectively manipulate a shape of the polygon. A user can add/delete vertices from the polygon as desired. The area of the image encompassed by the polygon is communicated to a breast cancer screening algorithm performing automated or semi-automated screening.

Automatic segmentation of breast tissue in a thermographic image

What is disclosed is a software tool which enables medical practitioners to manually or automatically analyze a thermal image of an area of breast tissue for the presence of tumorous tissue. In one embodiment, the software interface tool disclosed herein comprises a patient details object which enables the display of a patient details screen wherein a user can enter/edit patient information. A thermal analysis object enables a user to analyze a displayed thermal image of a breast of a patient for breast cancer screening and to classify tissue identified in the thermal image as being tumorous. A modalities object concludes the patient evaluation, persists all data collected from other sections of the tool, and generates reports for documentation purposes. The information can be captured from a database and edited and analyzed further using the tool. Also, report containing all the relevant data is generated for doctor's reference.

Software tool for breast cancer screening

What is disclosed is a system and method for contour-based determination of malignant tissue in a thermal image of a patient for cancer screening. In one embodiment, the method involves receiving a thermal image for cancer screening. Pixels in the thermal image with a higher temperature value are displayed in a first color and pixels with a lower temperature value are displayed in a second color. Pixels with temperature values between the lower and higher temperature values are displayed in gradations of color between the first and second colors. The thermal image is then analyzed to identify a patch of pixels with an elevated temperature relative to a temperature of pixels associated with surrounding tissue. Thereafter, tissue associated with the identified patch is determined to be malignant or non-malignant based a measure of irregularity calculated for boundary contour encompassing that patch of pixels.

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Andhra Pradesh, India

Siva Teja Kakileti